The present invention relates to computing systems, and more particularly to a system and method for efficiently processing digital documents.
Document search and compilation is needed in various business and personal matters. For example, when one purchases a house the transaction is conducted via an escrow company. A mortgage company, before releasing funds to complete the house sale, requires that the title to the property is valid and clear from any liability. Hence a title insurance company often conducts or orders a title search for the property. Often a search company collects documents from various disparate sources and compiles the information to prepare a search report. Some of these sources (or data providers) provide data and/or images electronically to facilitate automated results. Similar searches are performed in other business, legal, and other situations. For example, similar searches may be performed for due diligence in mergers and acquisitions; and employment background checks.
Conventional search systems continue to use manual labor and inefficient archaic systems and methodologies. A fully integrated/automated system that receives a customer request and efficiently delivers a customized report (or product) is commercially unavailable.
Automation today provides the ability to access enormous databases with millions of records on a wide variety of subjects. Automation also provides millions of documents and images containing a vast array and amount of information. Information stored in these documents and images includes names, addresses, historical data, financial data, property data, and other items that cannot be isolated or extracted using an automated process. This extraction process is performed manually and individually. The process is both cumbersome and cost prohibitive. Examples of documents subjected to this process include, property records, legal records, resumes, and other documents.
Title insurance, escrow, legal, and other companies currently spend millions of dollars and countless man hours each year isolating and extracting data elements from existing digital documents for further data processing or inclusion in other documents (for example, title search reports).
Optical Character Recognition (“OCR”) is an existing technology that converts document images into a text format allowing the document to be saved and viewed as a digital document. Information from documents that have undergone the OCR process (OCRed) may be extracted and used in other processes. Although OCR recognizes individual characters and can combine those into meaningful text, it does not allow or provide for automated extraction of data elements from digital documents.
Therefore, there is a need for a system and method that can efficiently extract useful information from digital documents based on customer needs and requirements.